SBIR/STTR Research Award

Improving data capture in clinical research using a chatbot

Award identifier 66fb3af17495e4e2f226ef801593c23e4e109acbd9f0115f89b1bc0e9951d3e8Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$252,130

Program and phase

STTR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Dokbot, LLC
Proposal award date
2020-09-08
Contract end date
2021-09-07
UEI
R571DMMP65J4
Solicitation number
PA19-270
Topic code
NLM

Research abstract

PROJECT SUMMARY . Collecting complete and accurate outcome data directly from research participants is becoming increasingly important. Clinical researchers needs a cost-effective approach to capture high-quality patient-reported outcomes. Typically, data captured directly from participants is through self-administered questionnaires or through a human interviewer, each with their own advantages and disadvantages. An effective new data capture technology that can collect patient-reported outcomes with the engagement of human interviews at the cost of self-administered surveys would build tremendous capacity for clinical research. Dokbot, LLC and the Medical University of South Carolina (MUSC) have partnered to develop Dokbot, a simple, scalable chatbot that uses text-based conversations to collect data from clinical research participants using the browser on their mobile devices. Chatbots are an innovative and effective way to capture data for clinical research. Unfortunately, current chatbot technologies do not adequately support data capture in clinical research. Dokbot can be adapted to enhance data capture in clinical research. However, significant adaptation, improvement, and refinement is needed to extend and optimize Dokbot for it to ideally support clinical research. To achieve this, we first need to understand opportunities and barriers among clinical research stakeholders using Dokbot (Aim 1) and then adapt and iteratively refine a functional prototype of Dokbot for clinical research (Aim 2). By demonstrating the feasibility of Dokbot as a simple, low-cost approach for collecting data in clinical research settings, we will have a clear path to develop the technology, expertise, and evidence to make a significant impact on improving clinical data collection for research. With support through the STTR award, Dokbot could become an effective tool to help clinical researchers improve the quality and efficiency of data from research participantsPROJECT NARRATIVE . Data capture tools for clinical research that provide high-quality information at a low cost are needed. Dokbot is a simple, scalable tool that uses intuitive text-based conversations to collect data from patients. The goal of this project is to develop a functional prototype of Dokbot and demonstrate the feasibility as an approach for data collection in clinical research settings.

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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